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Detecting market crashes by analysing long-memory effects using high-frequency data

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  • E. Barany
  • M. P. Beccar Varela
  • I. Florescu
  • I. Sengupta

Abstract

It is well known that returns for financial data sampled with high frequency exhibit memory effects, in contrast to the behavior of the much celebrated log-normal model. Herein, we analyse minute data for several stocks over a seven-day period which we know is relevant for market crash behavior in the US market, March 10--18, 2008. We look at the relationship between the L�vy parameter α characterizing the data and the resulting H parameter characterizing the self-similar property. We give an estimate of how close this model is to a self-similar model.

Suggested Citation

  • E. Barany & M. P. Beccar Varela & I. Florescu & I. Sengupta, 2012. "Detecting market crashes by analysing long-memory effects using high-frequency data," Quantitative Finance, Taylor & Francis Journals, vol. 12(4), pages 623-634, April.
    • Handle: RePEc:taf:quantf:v:12:y:2012:i:4:p:623-634
    DOI: 10.1080/14697688.2012.664937
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    References listed on IDEAS

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    1. Olan Henry, 2002. "Long memory in stock returns: some international evidence," Applied Financial Economics, Taylor & Francis Journals, vol. 12(10), pages 725-729.
    2. Marc Potters & Jean-Philippe Bouchaud, 2001. "More stylized facts of financial markets: leverage effect and downside correlations," Science & Finance (CFM) working paper archive 29960, Science & Finance, Capital Fund Management.
    3. Mariani, M.C. & Florescu, I. & Beccar Varela, M.P. & Ncheuguim, E., 2010. "Study of memory effects in international market indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(8), pages 1653-1664.
    4. Mariani, M.C. & Liu, Y., 2007. "Normalized truncated Levy walks applied to the study of financial indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 377(2), pages 590-598.
    5. Bouchaud, Jean-Philippe & Potters, Marc, 2001. "More stylized facts of financial markets: leverage effect and downside correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 60-70.
    6. Mariani, M.C. & Florescu, I. & Beccar Varela, M.P. & Ncheuguim, E., 2009. "Long correlations and Levy models applied to the study of memory effects in high frequency (tick) data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1659-1664.
    7. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
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    Cited by:

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    2. Maria C. Mariani & Peter K. Asante & Md Al Masum Bhuiyan & Maria P. Beccar-Varela & Sebastian Jaroszewicz & Osei K. Tweneboah, 2020. "Long-Range Correlations and Characterization of Financial and Volcanic Time Series," Mathematics, MDPI, vol. 8(3), pages 1-18, March.
    3. Rodríguez-Aguilar, Román & Cruz-Aké, Salvador & Venegas-Martínez, Francisco, 2014. "A Measure of Early Warning of Exchange-Rate Crises Based on the Hurst Coefficient and the Αlpha-Stable Parameter," MPRA Paper 59046, University Library of Munich, Germany.
    4. Zhidong Bai & Hua Li & Michael McAleer & Wing-Keung Wong, 2015. "Stochastic dominance statistics for risk averters and risk seekers: an analysis of stock preferences for USA and China," Quantitative Finance, Taylor & Francis Journals, vol. 15(5), pages 889-900, May.
    5. Mariani, M.C. & Florescu, I. & SenGupta, I. & Beccar Varela, M.P. & Bezdek, P. & Serpa, L., 2013. "Lévy models and scale invariance properties applied to Geophysics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 824-839.

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